详情

原文传递 Estimating Intersection Control Delay Using Large Data Sets of Travel Time from a Global Positioning System.

题名：	Estimating Intersection Control Delay Using Large Data Sets of Travel Time from a Global Positioning System.
作者：	Hoeschen-Brian; Bullock-Darcy; Schlappi-Mark
关键词：	Algorithms-; Berkeley-California; Field-studies; Freeways-; Headways-; Intersections-; Magnetic-detectors; Real-time-information; Speed-; Traffic-counts; Traffic-measurement; Traffic-platooning; Vehic
摘要：	Wireless magnetic sensor networks offer an attractive, low-cost alternative to inductive loops for traffic measurement in freeways and at intersections. In addition to providing vehicle count, occupancy, and speed, these sensors yield information (such as non-axle-based vehicle classification) that cannot be obtained from standard loop data. Because such networks can be deployed quickly, they can be used (and reused) for temporary traffic measurement. This paper reports the detection capabilities of magnetic sensors on the basis of two field experiments. The first experiment collected a 2-h trace of measurements on Hearst Avenue in Berkeley, California. The vehicle detection rate was better than 99% (100% for vehicles other than motorcycles), and estimates of average vehicle length and speed appear to have been better than 90%. The measurements also yield intervehicle spacing or headways, revealing interesting phenomena such as platoon formation downstream of a traffic signal. Results of the second experiment are preliminary. Sensor data from 37 passing vehicles at the same site are processed and classified into six types. Sixty percent of the vehicles are classified correctly when length is not used as a feature. The classification algorithm can be implemented in real time by the sensor node itself, in contrast to other methods based on high-scan-rate inductive loop signals, which require extensive off-line computation. It is believed that if length were used as a feature, 80% to 90% of vehicles would be correctly classified.
总页数：	Transportation Research Record: Journal of the Transportation Research Board. 2005. (1917) pp173-181 (11 Fig., 2 Tab., 10 Ref.)
报告类型：	科技报告